Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add meta-quest/agentic-tools --skill hz-unity-device-readinessgit clone --depth 1 https://github.com/meta-quest/agentic-toolsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/meta-quest/agentic-tools/hz-unity-device-readiness)<a href="https://agentmods.dev/skills/meta-quest/agentic-tools/hz-unity-device-readiness"><img src="https://agentmods.dev/badge/skills/meta-quest/agentic-tools/hz-unity-device-readiness/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/meta-quest/agentic-tools/hz-unity-device-readiness"><img src="https://agentmods.dev/badge/skills/meta-quest/agentic-tools/hz-unity-device-readiness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00069 | $0.02194 |
| Opus 5.5 | $0.00028 | $0.00878 |
| Sonnet 5.5 | $0.00014 | $0.00439 |
| Haiku 4.5 | $0.00007 | $0.00219 |
Grade A, and why
hz-unity-device-readiness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 24d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Device Readiness
Context
This skill prepares a Unity project for Meta VR Glasses device requirements across two dimensions: input (hand tracking as the primary input, not a fallback) and field of view (a device with a narrower FoV than current Quest headsets). The input workflow is immediately below; the field-of-view workflow is its own section further down.
The target device treats hand tracking as the primary input method, not a fallback. Most existing Quest projects were built controller-first, so the work isn't just "replace button presses with gestures" — it's rethinking interaction design so hands feel natural instead of like a worse controller. A systematic scan matters: find every controller dependency, understand the gameplay intent behind it, and map it to the right ISDK pattern.
When a Meta VR Glasses or Meta Quest device is connected, ground the audit in real device data first — metavr device list shows what's attached, and metavr device info <id> reports the device's input and display capabilities the audit should target.
Analysis Workflow
Step 1: Scan the Project
Build a complete picture of how the project handles input today. Controller dependencies hide in surprising places — not just obvious OVRInput.Get() calls, but also XR Interaction Toolkit components, Unity's legacy Input system, and custom grab systems. Cast a wide net:
# Find controller input usage
grep -r "OVRInput\.\(Get\|GetDown\|GetUp\)" --include="*.cs" .
grep -r "OVRInput\.Button\|OVRInput\.Axis" --include="*.cs" .
# Find XR Interaction Toolkit usage
grep -r "XRGrabInteractable\|XRRayInteractor\|XRDirectInteractor" --include="*.cs" .
# Find legacy Input system usage
grep -r "Input\.GetButton\|Input\.GetAxis\|Input\.GetKey" --include="*.cs" .
# Find interaction patterns
grep -r "Grabbable\|IGrabbable\|OnGrab\|OnRelease" --include="*.cs" .
grep -r "Raycast\|RaycastHit\|Physics\.Raycast" --include="*.cs" .
Step 2: Categorize Findings
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 24d ago First seen · 143 lines · 69 tokens per session scan A 3e249fedc58f
hz-unity-device-readiness is a skill published in the GitHub repository meta-quest/agentic-tools (221 stars, last pushed 25d ago), licensed Apache-2.0. It adds 69 tokens to every session and 2,194 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-25.
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